Recent Advances of Curcumin in the Prevention and Treatment of Renal Fibrosis
Bibliographic record
Abstract
Curcumin, a polyphenol derived from the turmeric, has received attention as a potential treatment for renal fibrosis primarily because it is a relatively safe and inexpensive compound that contributes to kidney health. Here, we review the literatures on the applications of curcumin in resolving renal fibrosis in animal models and summarize the mechanisms of curcumin and its analogs (C66 and (1E,4E)-1,5-bis(2-bromophenyl) penta-1,4-dien-3-one(B06)) in preventing inflammatory molecules release and reducing the deposition of extracellular matrix at the priming and activation stage of renal fibrosis in animal models by consulting PubMed and Cnki databases over the past 15 years. Curcumin exerts antifibrotic effect through reducing inflammation related factors (MCP-1, NF-κB, TNF-α, IL-1β, COX-2, and cav-1) and inducing the expression of anti-inflammation factors (HO-1, M6PRBP1, and NEDD4) as well as targeting TGF-β/Smads, MAPK/ERK, and PPAR-γ pathways in animal models. As a food derived compound, curcumin is becoming a promising drug candidate for improving renal health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".